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In a previous article (Faaß et al., 2012), a first attempt was made at documenting and encoding morphemic units of two South African Bantu languages, i.e. Northern Sotho and Zulu, with the aim of describing and storing the morphemic units of these two languages in a single relational database, structured as a hierarchical ontology. As a follow-up, the current article describes the implementation of our part-of-speech ontology. We give a detailed description of the morphemes and categories contained in the database, highlighting the need and reasons for a flexible ontology which will provide for both language specific and general linguistic information. By giving a detailed account of the methodology for the population of the database, we provide linguists from other Bantu languages with a road map for extending the database to also include their languages of specialization.
Towards a part-of-speech ontology: encoding morphemic units of two South African Bantu languages
(2012)
This article describes the design of an electronic knowledge base, namely a morpho-syntactic database structured as an ontology of linguistic categories, containing linguistic units of two related languages of the South African Bantu group: Northern Sotho and Zulu. These languages differ significantly in their surface orthographies, but are very similar on the lexical and sub-lexical levels. It is therefore our goal to describe the morphemes of these languages in a single common database in order to outline and interpret commonalities and differences in more detail. Moreover, the relational database which is developed defines the underlying morphemic units (morphs) for both languages. It will be shown that the electronic part-of-speech ontology goes hand in hand with part-of-speech tagsets that label morphemic units. This database is designed as part of a forthcoming system providing lexicographic and linguistic knowledge on the official South African Bantu languages.
Ein multilinguales linguistisches Begriffssystem wird in Form einer Datenbank implementiert, die dem Benutzer den semasiologischen und onomasiologischen Zugriff erlaubt, ihn also zu einem gegebenen Terminus den Begriff und seine Definition und zu einem gegebenen Begriff die Termini in den beteiligten Sprachen finden lässt. Die Mehrfachzuordnung von Begriffen zu Termini ist dabei auf interlingualer Ebene nicht wesentlich verschieden von der Situation in einer monolingualen Ontologie. Für die Normierung einer interlingualen Ontologie werden Grundsätze zur Bildung von Begriffen und von Termini vorgeschlagen. Zwischen den Begriffen bestehen eine Menge von vordefinierten konzeptuellen Relationen, die sie in systematische Beziehungen zueinander setzen und es sowohl dem Verwalter ermöglichen, das System konsistent zu halten, als auch dem Benutzer, im Begriffssystem zu navigieren.
Knowledge in textual form is always presented as visually and hierarchically structured units of text, which is particularly true in the case of academic texts. One research hypothesis of the ongoing project Knowledge ordering in texts - text structure and structure visualisations as sources of natural ontologies1 is that the textual structure of academic texts effectively mirrors essential parts of the knowledge structure that is built up in the text. The structuring of a modern dissertation thesis (e.g. in the form of an automatically generated table of contents - toes), for example, represents a compromise between requirements of the text type and the methodological and conceptual structure of its subject-matter. The aim of the project is to examine how visual-hierarchical structuring systems are constructed, how knowledge structures are encoded in them, and how they can be exploited to automatically derive ontological knowledge for navigation, archiving, or search tasks. The idea to extract domain concepts and semantic relations mainly from the structural and linguistic information gathered from tables of contents represents a novel approach to ontology learning.
In the project SemDok (Generic document structures in linearly organised texts) funded by the German Research Foundation DFG, a discourse parser for a complex type (scientific articles by example), is being developed. Discourse parsing (henceforth DP) according to the Rhetorical Structure Theory (RST) (Mann and Taboada, 2005; Marcu, 2000) deals with automatically assigning a text a tree structure in which discourse segments and rhetorical relations between them are marked, such as Concession. For identifying the combinable segments, declarative rules are employed, which describe linguistic and structural cues and constraints about possible combinations by referring to different XML annotation layers of the input text, and external knowledge bases such as a discourse marker lexicon, a lexico-semantic ontology (later to be combined with a domain ontology), and an ontology of rhetorical relations. In our text-technological environment, the obvious choice of formalism to represent such ontologies is OWL (Smith et al., 2004). In this paper, we describe two OWL ontologies and how they are consulted from the discourse parser to solve certain tasks within DP. The first ontology is a taxononomy of rhetorical relations which was developed in the project. The second one is an OWL version of GermaNet, the model of which we designed together with our project partners.
The administration of electronic publication in the Information Era congregates old and new problems, especially those related with Information Retrieval and Automatic Knowledge Extraction. This article presents an Information Retrieval System that uses Natural Language Processing and Ontology to index collection’s texts. We describe a system that constructs a domain specific ontology, starting from the syntactic and semantic analyses of the texts that compose the collection. First the texts are tokenized, then a robust syntactic analysis is made, subsequently the semantic analysis is accomplished in conformity with a metalanguage of knowledge representation, based on a basic ontology composed of 47 classes. The ontology, automatically extracted, generates richer domain specific knowledge. It propitiates, through its semantic net, the right conditions for the user to find with larger efficiency and agility the terms adapted for the consultation to the texts. A prototype of this system was built and used for the indexation of a collection of 221 electronic texts of Information Science written in Portuguese from Brazil. Instead of being based in statistical theories, we propose a robust Information Retrieval System that uses cognitive theories, allowing a larger efficiency in the answer to the users queries.
The main objective of this article is to describe the current activities at the Mannheim Institute for German Language regarding the implementation of a domain-specific ontology for German grammar. We differentiate ontology bases from ontology management Systems, point out the benefits of database-driven Solutions, and go Step by Step through all phases of the ontology lifecycle. In Order to demonstrate the practical use of our approach, we outline the interface between our ontology and the grammis web Information System, and compare the ontology-based retrieval mechanism with traditional full text search.
Linguistische Annotationen für die Analyse von Gliederungsstrukturen wissenschaftlicher Texte
(2012)
Researchers in many disciplines, sometimes working in close cooperation, have been concerned with modeling textual data in order to account for texts as the prime information unit of written communication. The list of disciplines includes computer science and linguistics as well as more specialized disciplines like computational linguistics and text technology. What many of these efforts have in common is the aim to model textual data by means of abstract data types or data structures that support at least the semi-automatic processing of texts in any area of written communication.